Artificial Intelligence (AI) is carrying out a lot of attacks in healthcare, predicting a heart attack before reading scans rapidly than doctors to a heart attack. Hospitals, clinics and pharmaceutical companies are using AI tools to save time, reduce costs and improve accuracy. It seems that a dream comes true, until you see the other side of the story.

While AI promises smart medicine, it not only brings our privacy, but also hidden threats to our health and environment.

Let’s start with positivity. AI systems today can help doctors to identify cancer tumors during colonoscopy, differentiate between pancreatitis and pancreatic cancer, and even help in complex surgery with robot weapons that move with accuracy.

In the world of tech, virtual counseling and AI-operated therapy platforms are also making healthcare more accessible to people in remote areas.

Environmental cost

But all this computing power comes with a heavy environmental value. The large -scale data centers who train and run the AI ​​model consume large amounts of electricity and water to stay cool.

According to the United Nations Environment Program (UNEP), data centers produce electronic waste mountains, often containing toxic materials such as mercury and lead. When dumped improperly, these chemicals can leak into soil and water, causing prolonged health risk such as respiratory diseases and neurological problems.

There is another problem: raw materials. The power AI system produces rare earth elements for the manufacture of microchips that mined in methods that damage the ecosystem and damage the nearby communities.

Construction of a single 2-cylogram computer requires approximately 800 kg of raw materials. It is an invisible chain of pollution associated with every “smart” medical tool that we celebrate.

Cost of health

The relationship between AI’s environmental footprint and human health is often ignored. When the e-waste is burnt or left to lower, it leaves harmful gases and fine particles in the air.

Prolonged contact for these pollutants can trigger developmental problems in asthma, heart disease and even children. Mining for the rare Earth metals required to create AI chips also contaminates groundwater and food sources, causing cancer, hormonal imbalances, and the risk of reproductive issues in the nearby population.

The same technique created to improve healthcare can indirectly harm those who have to protect it.

Another research from Stanford University published in June this year suggests that many AI therapy chatbots may introduce prejudices and failures that may result in dangerous consequences. They can show extended stigma towards alcohol dependence and schizophrenia, compared to conditions like depression.

Researchers say that such a stigma can be harmful to patients and may motivate them to stop significant mental health care.

AI in Healthcare also raises serious questions about data privacy and accountability. Electronic health records used to train the AI ​​system can be the major targets for hackers.

If personal health data is leaked, it can cause identity theft or exploitation by insurance companies, a significant assessment by researchers at NESBIT School of Pharmacy Wilks University, US.

AI in medicine is to live here, but we need to ensure that it is durable. This means that greenery data centers, strict data security rules, and moral structures that keep patient welfare above benefits.

Although we are in a crowd to make machines smart, we should not forget to keep our planet and ourselves healthy.